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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automated Algorithm Selection on Continuous Black-Box Problems by Combining Exploratory Landscape Analysis and Machine Learning
Pascal Kerschke, Heike Trautmann
Evolutionary Computation (2018) Vol. 27, Iss. 1, pp. 99-127
Open Access | Times Cited: 148

Showing 1-25 of 148 citing articles:

Benchmark for filter methods for feature selection in high-dimensional classification data
Andrea Bommert, Xudong Sun, Bernd Bischl, et al.
Computational Statistics & Data Analysis (2019) Vol. 143, pp. 106839-106839
Open Access | Times Cited: 544
Automated Algorithm Selection: Survey and Perspectives
Pascal Kerschke, Holger H. Hoos, Frank Neumann, et al.
Evolutionary Computation (2018) Vol. 27, Iss. 1, pp. 3-45
Open Access | Times Cited: 329
Machine Learning into Metaheuristics
El‐Ghazali Talbi
ACM Computing Surveys (2021) Vol. 54, Iss. 6, pp. 1-32
Closed Access | Times Cited: 112
Analyzing variational quantum landscapes with information content
Adrián Pérez-Salinas, Hao Wang, Xavier Bonet-Monroig
npj Quantum Information (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 7
Understanding the problem space in single-objective numerical optimization using exploratory landscape analysis
Urban Škvorc, Tome Eftimov, Peter Korošec
Applied Soft Computing (2020) Vol. 90, pp. 106138-106138
Open Access | Times Cited: 67
Landscape-Aware Performance Prediction for Evolutionary Multiobjective Optimization
Arnaud Liefooghe, Fabio Daolio, Sebástien Vérel, et al.
IEEE Transactions on Evolutionary Computation (2019) Vol. 24, Iss. 6, pp. 1063-1077
Open Access | Times Cited: 65
A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks
Ye Tian, Shichen Peng, Xingyi Zhang, et al.
IEEE Transactions on Artificial Intelligence (2020) Vol. 1, Iss. 1, pp. 5-18
Closed Access | Times Cited: 62
Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy
Quentin Renau, Carola Doerr, Johann Dréo, et al.
Lecture notes in computer science (2020), pp. 139-153
Open Access | Times Cited: 51
Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection
Moritz Vinzent Seiler, Urban Škvorc, Carola Doerr, et al.
Lecture notes in computer science (2025), pp. 361-376
Closed Access
Explainable Benchmarking for Iterative Optimization Heuristics
Bas van Stein, Diederick Vermetten, Anna V. Kononova, et al.
ACM Transactions on Evolutionary Learning and Optimization (2025)
Open Access
“Optimizing the Optimization”: A Hybrid Evolutionary-Based AI Scheme for Optimal Performance
Agathoklis A. Krimpenis, Loukas Athanasakos
Computers (2025) Vol. 14, Iss. 3, pp. 97-97
Open Access
A causal framework for stochastic local search optimization algorithms
Alberto Franzin, Thomas Stützle
Computers & Operations Research (2025), pp. 107050-107050
Closed Access
Learning the characteristics of engineering optimization problems with applications in automotive crash
Fu Xing Long, Bas van Stein, Moritz Frenzel, et al.
Proceedings of the Genetic and Evolutionary Computation Conference (2022), pp. 1227-1236
Open Access | Times Cited: 23
Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches
Mohamad Alissa, Kevin Sim, Emma Hart
Journal of Heuristics (2023) Vol. 29, Iss. 1, pp. 1-38
Open Access | Times Cited: 13
Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python
Raphael Patrick Prager, Heike Trautmann
Evolutionary Computation (2023) Vol. 32, Iss. 3, pp. 211-216
Closed Access | Times Cited: 13
MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts
Diederick Vermetten, Furong Ye, Thomas Bäck, et al.
ACM Transactions on Evolutionary Learning and Optimization (2024) Vol. 5, Iss. 1, pp. 1-19
Open Access | Times Cited: 4
Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions
Quentin Renau, Johann Dréo, Carola Doerr, et al.
Lecture notes in computer science (2021), pp. 17-33
Open Access | Times Cited: 27
Transfer Learning Analysis of Multi-Class Classification for Landscape-Aware Algorithm Selection
Urban Škvorc, Tome Eftimov, Peter Korošec
Mathematics (2022) Vol. 10, Iss. 3, pp. 432-432
Open Access | Times Cited: 18
Exploratory Landscape Validation for Bayesian Optimization Algorithms
T.A. Agasiev, Anatoly Karpenko
Mathematics (2024) Vol. 12, Iss. 3, pp. 426-426
Open Access | Times Cited: 3
New features for continuous exploratory landscape analysis based on the SOO tree
Bilel Derbel, Arnaud Liefooghe, Sebástien Vérel, et al.
(2019), pp. 72-86
Open Access | Times Cited: 32
A new taxonomy of global optimization algorithms
Jörg Stork, A. E. Eiben, Thomas Bartz–Beielstein
Natural Computing (2020) Vol. 21, Iss. 2, pp. 219-242
Open Access | Times Cited: 28
Improving the state-of-the-art in the Traveling Salesman Problem: An Anytime Automatic Algorithm Selection
Isaías I. Huerta, Daniel A. Neira, Daniel A. Ortega, et al.
Expert Systems with Applications (2021) Vol. 187, pp. 115948-115948
Closed Access | Times Cited: 26
Towards Feature-Based Performance Regression Using Trajectory Data
Anja Jankovič, Tome Eftimov, Carola Doerr
Lecture notes in computer science (2021), pp. 601-617
Open Access | Times Cited: 24
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization
Christian Grimme, Pascal Kerschke, Pelin Aspar, et al.
Computers & Operations Research (2021) Vol. 136, pp. 105489-105489
Open Access | Times Cited: 24
Single- and multi-objective game-benchmark for evolutionary algorithms
Vanessa Volz, Boris Naujoks, Pascal Kerschke, et al.
Proceedings of the Genetic and Evolutionary Computation Conference (2019), pp. 647-655
Closed Access | Times Cited: 28
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